| --- |
| annotations_creators: |
| - expert-generated |
| language_creators: |
| - expert-generated |
| language: |
| - pl |
| license: |
| - unknown |
| multilinguality: |
| - monolingual |
| size_categories: |
| - 1K<n<10K |
| source_datasets: |
| - original |
| task_categories: |
| - text-retrieval |
| task_ids: |
| - entity-linking-retrieval |
| pretty_name: bprec |
| dataset_info: |
| - config_name: default |
| features: |
| - name: id |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: tele |
| num_bytes: 2739015 |
| num_examples: 2391 |
| - name: electro |
| num_bytes: 125999 |
| num_examples: 382 |
| - name: cosmetics |
| num_bytes: 1565263 |
| num_examples: 2384 |
| - name: banking |
| num_bytes: 446944 |
| num_examples: 561 |
| download_size: 8006167 |
| dataset_size: 4877221 |
| - config_name: all |
| features: |
| - name: id |
| dtype: int32 |
| - name: category |
| dtype: string |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: train |
| num_bytes: 4937658 |
| num_examples: 5718 |
| download_size: 8006167 |
| dataset_size: 4937658 |
| - config_name: tele |
| features: |
| - name: id |
| dtype: int32 |
| - name: category |
| dtype: string |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: train |
| num_bytes: 2758147 |
| num_examples: 2391 |
| download_size: 4569708 |
| dataset_size: 2758147 |
| - config_name: electro |
| features: |
| - name: id |
| dtype: int32 |
| - name: category |
| dtype: string |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: train |
| num_bytes: 130205 |
| num_examples: 382 |
| download_size: 269917 |
| dataset_size: 130205 |
| - config_name: cosmetics |
| features: |
| - name: id |
| dtype: int32 |
| - name: category |
| dtype: string |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: train |
| num_bytes: 1596259 |
| num_examples: 2384 |
| download_size: 2417388 |
| dataset_size: 1596259 |
| - config_name: banking |
| features: |
| - name: id |
| dtype: int32 |
| - name: category |
| dtype: string |
| - name: text |
| dtype: string |
| - name: ner |
| sequence: |
| - name: source |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| - name: target |
| struct: |
| - name: from |
| dtype: int32 |
| - name: text |
| dtype: string |
| - name: to |
| dtype: int32 |
| - name: type |
| dtype: |
| class_label: |
| names: |
| '0': PRODUCT_NAME |
| '1': PRODUCT_NAME_IMP |
| '2': PRODUCT_NO_BRAND |
| '3': BRAND_NAME |
| '4': BRAND_NAME_IMP |
| '5': VERSION |
| '6': PRODUCT_ADJ |
| '7': BRAND_ADJ |
| '8': LOCATION |
| '9': LOCATION_IMP |
| splits: |
| - name: train |
| num_bytes: 453119 |
| num_examples: 561 |
| download_size: 749154 |
| dataset_size: 453119 |
| --- |
| |
| # Dataset Card for [Dataset Name] |
|
|
| ## Table of Contents |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** [bprec homepage](https://clarin-pl.eu/dspace/handle/11321/736) |
| - **Repository:** [bprec repository](https://gitlab.clarin-pl.eu/team-semantics/semrel-extraction) |
| - **Paper:** [bprec paper](https://www.aclweb.org/anthology/2020.lrec-1.233.pdf) |
| - **Leaderboard:** |
| - **Point of Contact:** |
|
|
| ### Dataset Summary |
|
|
| Brand-Product Relation Extraction Corpora in Polish |
|
|
| ### Supported Tasks and Leaderboards |
|
|
| NER, Entity linking |
|
|
| ### Languages |
|
|
| Polish |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| [More Information Needed] |
|
|
| ### Data Fields |
|
|
| - id: int identifier of a text |
| - text: string text, for example a consumer comment on the social media |
| - ner: extracted entities and their relationship |
| - source and target: a pair of entities identified in the text |
| - from: int value representing starting character of the entity |
| - text: string value with the entity text |
| - to: int value representing end character of the entity |
| - type: one of pre-identified entity types: |
| - PRODUCT_NAME |
| - PRODUCT_NAME_IMP |
| - PRODUCT_NO_BRAND |
| - BRAND_NAME |
| - BRAND_NAME_IMP |
| - VERSION |
| - PRODUCT_ADJ |
| - BRAND_ADJ |
| - LOCATION |
| - LOCATION_IMP |
| |
| |
| ### Data Splits |
| |
| No train/validation/test split provided. Current dataset configurations point to 4 domain categories for the texts: |
| - tele |
| - electro |
| - cosmetics |
| - banking |
| |
| ## Dataset Creation |
| |
| ### Curation Rationale |
| |
| [More Information Needed] |
| |
| ### Source Data |
| |
| #### Initial Data Collection and Normalization |
| |
| [More Information Needed] |
| |
| #### Who are the source language producers? |
| |
| [More Information Needed] |
| |
| ### Annotations |
| |
| #### Annotation process |
| |
| [More Information Needed] |
| |
| #### Who are the annotators? |
| |
| [More Information Needed] |
| |
| ### Personal and Sensitive Information |
| |
| [More Information Needed] |
| |
| ## Considerations for Using the Data |
| |
| ### Social Impact of Dataset |
| |
| [More Information Needed] |
| |
| ### Discussion of Biases |
| |
| [More Information Needed] |
| |
| ### Other Known Limitations |
| |
| [More Information Needed] |
| |
| ## Additional Information |
| |
| ### Dataset Curators |
| |
| [More Information Needed] |
| |
| ### Licensing Information |
| |
| [More Information Needed] |
| |
| ### Citation Information |
| ``` |
| @inproceedings{inproceedings, |
| author = {Janz, Arkadiusz and Kopociński, Łukasz and Piasecki, Maciej and Pluwak, Agnieszka}, |
| year = {2020}, |
| month = {05}, |
| pages = {}, |
| title = {Brand-Product Relation Extraction Using Heterogeneous Vector Space Representations} |
| } |
| ``` |
| |
| ### Contributions |
| |
| Thanks to [@kldarek](https://github.com/kldarek) for adding this dataset. |
